Lecturer, Faculty of Integrated Technologies
I am Dr. Veena Raj working as a lecturer in (Info communication System) at Faculty of Integrated Technologies, Universiti Brunei Darussalam since Dec 2020. I have completed my Bachelor’s degree in Electronics & Communication from Anna University, Chennai, India and completed the Master’s Degree in Applied Electronics from same University. These academic trainings motivated me to do further research and I have completed my Doctoral degree in System Engineering from the Faculty of Integrated Technology, University of Brunei Darussalam. Focus of my research was on Application of Artificial Intelligence in designing and managing Renewable energy systems.
I have keen interest in applying various Machine Learning methods to resolve complex real life problems. In my Doctoral research, I have developed a short-term wind power forecasting system which can predict the performance of large wind farms with an impressive accuracy level. The hybrid system integrated Numerical Weather Prediction model with wind farm and turbine models to forecast the productivity of wind farms in shorter time intervals. The developed method, with the novel concept of cascaded input approach, was successfully applied in performance modelling of a large wind farm in Europe.
With my keen interest in teaching, I have served for four years as an Assistant Professor at Musaliar College of Engineering, Kerala, India, which is a constituent college at the Mahatma Gandhi University, Kerala, India. I could offer several courses for the undergraduate and graduate students in different departments. Several student research projects were also supervised during this period. I was also worked as a Program Analyst in a reputed Multinational company. During my days of research at UBD, I was actively involved in the UBD IBM Centre where I was working as a core member on various applications of machine learning in the smart management of renewable energy systems, which was a research collaboration between the Universiti Brunei Darussalam and IBM, Apart from contributing to different projects undertaken by the Centre, I also assisted in supervising four student’s project, which were attached to the Centre.
Ph.D in Systems Engineering
Master of Engineering in Applied Electronics
Bachelors of Engineering in Electronics and Communication
Artificial Intelligence, Machine Learning, Renewable Energy and Digital Image processing
Due to the growing environmental concerns and long-term challenges in energy security, global energy scenarios are shifting more towards sustainable and renewable energy resources With continued R&D initiatives, renewable energy technologies are rapidly becoming economically viable and will soon be able to compete with traditional energy options. This research focusses on applying the advances in artificial Intelligence (AI) and Machine Learning (ML) in the efficient design and intelligent management of renewable integrated energy systems. Renewable energy resources like solar and wind, available at prospective sites, are to be quantified based on the Numerical Weather Predictions (NWP), which are enhanced in spatial resolution using AI and ML methods. This can then be used for the optimal design of renewable energy systems suitable for the region of interest. Further, the designed renewable energy systems can be efficiently managed through the intelligent load and generation forecasting systems
Medical imaging, combined with advanced techniques in Artificial intelligence (AI), is being widely used in healthcare in the recent years. The data from the images provide clinicians with an abundant and intriguing source of information about patient’s health status. The computerized algorithms and pattern recognition abilities of AI are increasingly helping medical practitioners in making accurate diagnosis and effective treatment plans. The proposed research aims at developing innovative AI based image processing and interpretation methods, which can assist the clinicians in accurately identifying and managing the complex health issues of the patients.
One of the recent applications of Artificial Intelligence (AI) and Machine Learning (ML) is for the identification of suitable energy materials and their characterization for the development of efficient energy harvesting systems. AI based approaches can not only facilitate the optimal design and development of advanced energy materials but also can enhance the efficiency of their deployment and management. This research aims at developing appropriate AI and ML methods for identifying and characterizing suitable materials for energy system development. Emphasis of the project could be on the applications like solar photovoltaic systems, fuel cells and carbon dioxide capture materials.
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